The Advanced Camera for Surveys Virgo Cluster Survey. V. Surface Brightness Fluctuation Calibration for Giant and Dwarf Early‐Type Galaxies
Bibliographic record
Abstract
As part of the Advanced Camera for Surveys (ACS) Virgo Cluster Survey, we have measured surface brightness fluctuations (SBFs) in a sample of 100 early-type Virgo galaxies. Distances derived from these measurements are needed to explore the three-dimensional structure of the Virgo Cluster, study the intrinsic parameters of globular clusters associated with the program galaxies, and compare with the galaxy distances derived from globular cluster luminosity functions. Our SBF measurements have been performed in the F850LP bandpass of the Wide Field Channel of the ACS on the Hubble Space Telescope . These are the first measurements of this kind, and we present the first SBF calibration for this bandpass. The measured fluctuations depend on galaxy stellar population variations, which we quantify by galaxy color ( g 475 - z 850 ) 0 , where g 475 and z 850 are the galaxy magnitudes in the F475W and F850LP ACS filters, respectively. We derive the calibration for the absolute SBF magnitude 850 = -2.06 ± 0.04 + (2.0 ± 0.2)[( g 475 - z 850 ) 0 - 1.3] in the range 1.3 < ( g 475 - z 850 ) 0 ≤ 1.6, and 850 = -2.06 ± 0.04 + (0.9 ± 0.2)[( g 475 - z 850 ) 0 - 1.3] in the range 1.0 ≤ ( g 475 - z 850 ) 0 ≤ 1.3. The quoted zero-point uncertainty here includes all sources of internal error; there is an additional systematic uncertainty of ~0.15 mag, due to the uncertainty in the distance scale calibration. Physically, the two different color regimes correspond to different galaxy types: giant ellipticals and S0s at the red end, and early-type dwarfs at the blue end. For the first time in SBF studies, we are able to provide a firm empirical calibration of SBF in early-type dwarf galaxies. Our results agree with stellar population model predictions from Bruzual & Charlot in the range 1.3 < ( g 475 - z 850 ) 0 ≤ 1.6, while our empirical slope is somewhat steeper than the theoretical prediction in the range 0.9 ≤ ( g 475 - z 850 ) 0 ≤ 1.3.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".